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Datasets (11)
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System
This dataset contains approximate GIS (Geographic Information System) geospatial boundaries associated with each of the Grid Supply Points (GSPs) on the GB transmission network. The boundaries have…
- CSV
Demand
This dataset contains incremental updates for 2-52 weeks ahead demand forecast. The forecast assist the industry to make efficient decisions in balancing their supply and demand positions.
- CSV
Demand
The historic half hourly day ahead national demand forecast as published via BM reports, alongside the outturn values, adjustments for TRIAD avoidance estimates and Absolute Percentage Error (APE)…
- CSV
Demand
This dataset contains a preliminary list of Balancing Mechanism units that make up National Demand. This is related to the Historic Demand Data published here
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- GeoJSON
- PNG
System
This dataset contains approximate GIS (geographic information system) geospatial boundaries for each of the DNO License Areas in Great Britain. There are 14 licensed Distribution Network Operators (…
- DOC
- CSV
Demand
This section contains historic electricity demand, interconnector, hydro storage pumping, Non-BM Short Term Operating Reserve (STOR), wind and solar outturn data., Note, : We are currently…
- CSV
- PNG
Demand
This dataset contains national electricity demand forecast for day ahead as well as all historic day ahead demand forecasts. The forecast assist the industry to make efficient decisions in balancing…
- CSV
Demand
This dataset contains national electricity demand forecasts for 2-14 days ahead (medium term) as well as all historic 2-14 days ahead forecasts. These forecasts assist the industry to make efficient…
- CSV
Demand
This dataset contains the historical and forecast profile dates used to convert our Cardinal Point forecasts into half hourly demand forecasts between the start of 2018 up to 14 Days Ahead. The…
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Demand
This dataset contains national electricity demand forecast for 2 days ahead as well as all historic 2 day ahead demand forecasts. The forecast assist the industry to make efficient decisions in…
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